Course ID
Key schedule and booking details
Length 5 Days
Location online Fees £ 1850
Date 2026-05-25
OVERVIEW
In today’s data-driven world, raw numbers mean little without proper analysis. Whether you're working in business intelligence, finance, healthcare, or research, mastering data analysis methods and techniques gives you the power to uncover patterns, optimize processes, and drive strategic decisionmaking.
This course provides a hands-on, practical approach to data analysis, visualization, and statistical modeling using Python, Power BI, and Tableau. By the end, you’ll be confidently analyzing large datasets, building predictive models, and extracting actionable insights to support business growth and innovation.
You’ll Learn How To:
• Apply statistical analysis to extract meaningful trends.
Collect, clean, and structure data from multiple sources.
• Visualize data effectively using Python, Power BI, and Tableau.
• Implement advanced regression and forecasting techniques for predictive modeling.
• Leverage big data tools like Hadoop and Spark for large-scale analytics.
• Develop confidence intervals and probability models for risk assessment.
• If you've ever thought, "How can I master data analysis and use it to make smarter decisions?" this course is your opportunity to turn that question into expertise.
OBJECTIVES
By completing the Business Intelligence, Data Analysis, and Reporting Techniques course, you’ll develop a robust set of skills that will allow you to effectively manage and transform raw data into actionable business insights. You will gain expertise in:
Consolidating and validating data from multiple files and sheets for accurate analysis.
• Applying advanced Excel functions like SUMIFS, COUNTIFS, VLOOKUP, and array functions to manipulate and analyze data.
• Creating dynamic and informative pivot tables, allowing you to summarize and report data efficiently.
• Designing clear, structured, and visually appealing reports to communicate insights to stakeholders.
• Mastering data modeling techniques with tools like spinners, check boxes, option buttons, and scenario manager for better data analysis.
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• Linking Excel with external sources such as text files, SQL databases, and other Excel files to integrate diverse datasets.
IDEAL PARTICIPANTS
The Business Intelligence, Data Analysis, and Reporting Techniques course is perfect for:
• Project managers and team leaders responsible for overseeing projects and using data-driven insights to make strategic decisions.
Business analysts, data analysts, and financial analysts who work with large datasets and need to produce insightful reports.
• Professionals from finance, operations, or marketing departments who wish to optimize their data management and reporting workflows.
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• IT professionals who want to enhance their knowledge of data integration between various systems like Excel, SQL, and databases.
OUTLINE
DAY 1
Before we dive into complex models, we must build a strong foundation in data analysis. Today, we explore how to collect, clean, and structure data for meaningful insights. What is data analysis, and why is it crucial?
• Data sources & sampling techniques—ensuring accuracy in analysis.
• Setting up Python for data analysis—introducing key libraries like Pandas & NumPy.
• Creating simple data visualizations using Python & Power BI.
• Fundamental statistical measures—mean, median, variance, and standard deviation.
• Handling missing values & outliers—how to clean and preprocess messy data.
• Hands-on Session: Load, clean, and visualize a dataset using Python.
• DAY 2
How do we extract patterns from data? Today, we break down data mining, trend analysis, and correlation techniques to uncover hidden insights. Introduction to data mining—understanding its role in analytics.
• Types of data visualization:
• Single-Dimensional
• Two-Dimensional
• Multi-Dimensional
• Creating data visualizations using Python, Power BI, and Tableau.
• Conducting trend analysis—spotting patterns in time-series data.
• Box plots & whisker charts—interpreting data distributions.
• Correlation analysis—identifying relationships between variables.
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• Activity: Perform correlation analysis on a real-world dataset.
DAY 3
Visual storytelling is key—today, we master histograms, Pareto analysis, and big data visualization. What are histograms, and why do they matter?
• Creating histograms in Python, Power BI, and Tableau.
• Pareto analysis & cumulative percentage analysis—focusing on the most critical factors.
• Introduction to big data & Hadoop—how large-scale data processing works.
• Visualizing big data in Tableau and Power BI.
• Percentile analysis & the law of diminishing returns—understanding data distributions.
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• Hands-on Session: Build interactive dashboards for real-world datasets.
DAY 4
Predicting outcomes with regression models and curve fitting—a must-have skill for any data analyst. What is Fourier transform?—frequency analysis in data.
• Understanding periodic vs. aperiodic data.
• Regression techniques:
• Linear regression
• Non-linear regression
• Curve fitting
• Applying regression techniques in Power BI & Tableau.
• Introduction to Apache Spark—handling massive datasets.
• Predictive analytics—forecasting trends using machine learning models.
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• Practical Exercise: Develop a predictive model using Python and visualize the results.
DAY 5
Today, we dive into risk analysis, probability models, and complex analytics for decision-making. Understanding probability distributions—normal, binomial, Poisson.
• Calculating expected values & confidence intervals—setting data-driven benchmarks.
• Risk assessment & uncertainty analysis—how to handle unpredictable scenarios.
• Performing ANOVA (Analysis of Variance) in Python.
• Exploring pivot tables & Data Analysis Tool Pack in Excel—quick data manipulation.
• Big data analytics with Hadoop & Spark—how leading organizations process massive datasets.
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• Final Project: Conduct an end-to-end analysis, from data collection to visualization.
Will I receive course materials?
Yes, high-quality documentation is provided to all delegates.
Do you issue certificates?
An accredited Certificate of Completion is awarded upon successful completion.
What are the course timings?
09:00–12:45 or 13:00–17:00.
How do I register and pay?
Complete the registration form on the course page and select your preferred payment method.
What is your cancellation policy?
14 days from booking for a full refund or free transfer; exceptions apply on medical grounds.
Do you offer airport transfers?
Yes, airport pick-up and drop-off to/from the hotel can be arranged.
CONSULTING SERVICES
Tailored solutions for sustainable growth
At Regent Training Centre, we deliver consultancy services designed to help organisations overcome challenges and achieve sustainable growth through practical and results-driven strategies.
